This work discovers the underlying causal variables and their dependencies.
This is related to disentangling variables [1]} and disentangled representation learning [2]}, [3]}.
Some work points out that assumptions, including priors or biases, should be necessary to discover the underlying explanatory variables [1]}, [5]}.
Another work [5]} reviews and evaluates disentangling and discusses different metrics.
